Exporing differents abiotic data sources

Author

Vincent Bellavamce

Published

January 23, 2023

Bathymetry

Mean_bathy.tif from Beauchesne and bathymetry.tif from GEBCO

The scale of bathymetry.tif seems to be finer than bathy_mean.tif:

This is the differences between both datasets. Most of this difference must come from the different scale for both datasets.

Should we use other variables derived from bathymetry? (https://www.frontiersin.org/articles/10.3389/fmars.2021.652540/full)

  • slope

  • TPI (Topographic Position Index): difference between the value of a cell and the mean value of its 8 surrounding cells

  • TRI (Terrain Ruggedness Index): mean of the absolute differences between the value of a cell and the value of its 8 surrounding cells

  • roughness: difference between the maximum and the minimum value of a cell and its 8 surrounding cells

TPI seems quite uniform over the entire area of study, so maybe it’s not that relevant to use it. Slope, TRI and roughness seems strongly correlated. Let’s see:

           bathymetry      slope        TRI  roughness
bathymetry 1.00000000 0.02550875 0.01108015 0.01528311
slope      0.02550875 1.00000000 0.90531682 0.94775283
TRI        0.01108015 0.90531682 1.00000000 0.94613523
roughness  0.01528311 0.94775283 0.94613523 1.00000000

Since everything is strongly correlated, we should only use one of these three variables. Let’s use slope since it’s more intuitive to picture.

To summarize, for bathymetry and derivatives, we should use:

  • the bathymetry from GEBCO since the scale is finer and

  • the slope, since it’s strongly correlated with TRI and roughness and it’s more intuitive to picture.

Oxygen

  • oxygen_[2011-2020].tif from DFO

  • sat.tif from Beauchesne (I presume this is bottom dissolved oxygen from Blais 2019?)

  • bio-oracle dissolved oxygen

EGSL data from DFO seems incomplete (oxygen_[2011-2020].tif):

Oxygen saturation? from Blais 2019?

Dissolved oxygen is also available from bio-oracle:

Primary productivity

Since we’re modelling sea pens, should we focus on bottom primary production? If so, then we have two datasets for now:

  • present_benthic_mean_depth_primary_productivity_mean.tif from Beauchesne

  • bottom_primary_productivity.tif from bio-oracle

Is it relevant ot use if most of primary productivity seems to be near the coast and that sea pens are mostly deep in the water?

Salinity

There is two datasets of bottom salinity:

  • salinity_[2011-2020].tif from DFO

  • salmoymoy.tif from Beauchesne, from Dutil 2011?

Salinity from Beauchesne seems very “uniform” compared to DFO data. But there is a part missing for salinity_[2011-2020].tif northeast of the area of study.

Let’s see what bio-oracle salinity looks like (V2.2)

Temperature

We have two datasets:

  • temperature_[2011-2020].tif from DFO

  • sbt.tif from Beauchesne (I assume this is bottom temperature from Galbraith 2018?)

Again, there is a portion northeast of the area of study without any data for temperature_[2011-2020].tif.

The difference between both datasets seem minimal

Current velocity

Should we use current velocity since it can relate to anchoring ability of the sea pens (https://www.frontiersin.org/articles/10.3389/fmars.2021.652540/full).

Here are the min, mean and max current velocity at mean depth from bio-oracle.

I’m showing V2.1 because the minimum current velocity values in V2.2 are greater than mean current velocity, which seems odd.